Data analysis – Pagina 4

JOËL PIROE – SHOT ANALYSIS

Posted on 02/16/2022 by admin

Joël Piroe was known as a talent in the PSV academy, but after he moved to Wales, to play for Swansea City, many Dutch people made it out to be a weird move. He is off the radar and new talent has been given attention. The Dutch striker however is performing quite well in the Championship and that’s why I wanted to analyse his shooting stats and qualities in this article.

I will look at Piroe’s shots and analyse where they come from, how well he is doing, and whether he is one of the top strikers of the ball in the Championship. I will do that by looking at the shooting metrics compared to his peers, but also investigating more into his shots. The data and video come from Wyscout and were retrieved on February 16th, 2021.

In the scatterplot above we can see the metrics shots per 90 and expected goals per 90. It tells us how big the probability of a shot being converted into a goal is and the actual shots. We can assess how high the quality of a shot is and how likely it is that that particular shot will end up in a goal.

Piroe has an xG per 90 of 0,30 per 90 minutes from 2,57 shots taken per 90 minutes. It tells us how many goals Piero is likely to score every 90 minutes. With these metrics, he is doing quite well and performing above average in relation to his peers in the English Championship.

In the graphs below you can see the percentile ranks of Piroe compared to the 105 players in my database. This shows in which percentile he is for every metric that belongs to the shooting side of the game.

You can see that Piroe does very well in the shooting stats, especially when you look at the non-penalty goals per 90 and shots per 90 metrics. He scores above average in the other two metrics for shooting as well. If we look at the actual creating and possession metrics, he scores below average.

In the image above you can see a bee swarm plot. This visually shows us how Piroe is performing in relation to his peers, and how far ahead (or not) he is to his peers. It shows us the same data as in the percentile radar, but now in a different visual.

In the last of these comparison graphs, we see a comparison radar. We see the absolute values of the metrics of Piroe and compare them to the average values of these metrics within our database. Again, this shows us that Piroe is performing above average when you look at the shooting stats, but not so much in the other stats.

Shot locations

Credit: InStat

Looking at the shot map above we can see that Piroe has had 76 shots across all competitions, with 14 of those shots converted into a goal. That’s a conversion rate of 18,42%. In all those games he accumulated an expected goals ratio of 8,7. This means that he is overperforming his xG with +5,3. That’s a good sign.

A shot map over a season doesn’t say that much, and I wanted to illustrate where his shots come from in the last few games he has played. The last 4 actually, which you can see below.

So in the shot maps above you can see that Piroe has played amounts of minutes and not had many shots, but what we can see is that he shoots in and around the box in these particular games against Luton Town, Blackburn Rovers, Stoke City and Bristol City. What we also can see that he doesn’t shy away from trying to shoot from distance, which can explain the high volume of shots per 90 in comparison with his peers.

Video analysis

In the video above we see Swansea attacking in their game against Blackpool. It illustrated the area where Piroe loves to operate: zone 14. He remains a bit less progressive as his teammates as the attack is constructed and has more space to receive the ball. He claims the ball, wins the 1v1 and blasts the ball in the top corner with his right foot.

In the video above you see Swansea attacking in their game against Nottingham Forest. They move up the field and are trying to utilise the flanks and swing a cross into the six-yard box. While Piroe is a striker/attacker, he remains conservative in his position to anticipate any cleared/defended balls. This is no different in this case, as the cross is deflected. He doesn’t hesitate and volleys the ball – albeit deflected – into the top corner. An excellent strike from Piroe.

In the video you see Swansea attacking after regaining possession of the ball vs Bristol City. In the transition Swansea are in a 3v3 situation with Piroe on the ball. He has options to pass the ball and utilise the flanks, but he opts for the 1v1, wins it and creates space for himself in front of goal. His shot with his left foot is a success in which he drives it into the long corner, away from the keeper’s reach.

Final thoughts

Piroe has made a move to the Championship which might feel like a weird thing to do in the Netherlands when you were contracted at PSV, but for his development, it’s a good thing to do. He can be very important and can grow in a very competitive league. Judging his scoring numbers he also is finding his way and can be instrumental in any success the Swans might have on the pitch this season.

STINA BLACKSTENIUS – SHOT ANALYSIS BK HÄCKEN 2021

Posted on 01/13/2022 by admin

Stina Blackstenius has been the talk of the town in the land of the WSL. The Swedish striker has been linked with both Manchester United and Arsenal, with the latter having the biggest chance of signing here. Obviously, the striker has been doing well, but how was her shooting like in the 2021 Damallsvenskan? I will try to illustrate that in this article.

I will look at Blackstenius’ shots and analyse where they come from, how well she is doing, and whether she is a force to be reckoned with. I will do that by looking at the shooting metrics compared to her peers, but also investigating more into her shots. The data and video come from Wyscout and were retrieved on January 13th, 2021.

Data

Looking at shot quality can be measured in different things. In the scatterplots below I will look at the volume of the shots and the expected goals that are generated through the shots.

In the graph aboce you see the shots per 90 and shots on target metrics. When we look at this we see that Blackstenius does very well with 4,82 shots per 90 of which 42,7% go on target. She performs way above average in these metrics.

In the scatterplot above you can see the number of shots per 90 of a certain player and the expected goals per 90 of that particular player in question. The reason we look at this is how many shots a player has in a game and how high the probability is of scoring an actual goal.

In the shot volume, we can see that Blackstenius has 4,82 shots per 90 and the corresponding xG per 90 minutes for Blackstenius is 0,81.

In the end, the most important thing for a striker is his output: goals. I’m looking at the probability of scoring a goal with a certain short and looking at the actual goals scored by a particular player per 90 minutes.

Looking at the expected goals per 90 minutes we see that Blackstenius has 0,81 per 90 minutes, while as we look at the actual goals scored per 90 minutes, we see that that is 0,80 per 90 minutes. She is slightly underperforming but only with 0,01 per 90 minutes – which is insanely good.

In the graph below you can see the percentile ranks of Blackstenius compared to the 42 players in my database. This shows in which percentile he is for every metric that belongs to the shooting side of the game.

As you can see in the image above, Blackstenius scored very high in the shooting metrics. In the head goals per 90 she scores in the 72nd percentile, but in the shots per 90, xG per 90 and goals per 90 – she scored in the highest percentile: the 99th percentile. This means in terms of data she was the best striker of Damallsvenskan when looking at shooting stats.

Shot locations

Stina Blackstenius has scored 17 goals in Damallsvenskan 2021season from 103 shots in total. That is a goal conversion rate of 16,50%. The expected goal is 17,37 – which means that Blackstenius is slightly underperforming her xG with – 0,37. In the visual above you can see the shot locations of every shot attempted in the current season. In red, you see the goals, and in black the shots. The black dots correspond with shots on target, while the ‘x’ means a blocked shot or a shot wide.

Video analysis

In the last part of this shot analysis, I will look at four of Blackstenius’ goals which show different skill in each of the goals, and therefore shows the quality she has in this Damallsvenskan season.

In the video above you Blackstenius with BK Häcken in their game against Djurgårdens IF. This attack is not that direct, but it illustrates how Blackstenius likes to play on the off-side line and stay close to her marker, just before making a movement and having the space to create something. In this case she runs away from her marker, reaches the ball earlier than the goalkeeper and heads the ball over the goalkeeper in goal.

In the video above you seen Blackstenius with BK Häcken in their game against Rosengård. Not every attacking can be direct over the ground with dominant possession of the ball. Blackstenius is good at receiving the ball in the air and for the link up play as a target-woman. In this case she wants to receive the high ball, wins the duel and while she is out of balance, still manages to find the far corner with her right foot.

In the video above you Blackstenius with BK Häcken in their game against Växjö DFF. She is very good in the penalty area and can have close control of the ball to create space for herself and finish the ball. This is what she does in this example. She again knows how to control the ball and within a few touches knows how to set herself up and shoot. Her finish is outstanding in the way that she manages to put it in the top corner from a difficult angle.

In the video above you can see Blackstenius with BK Häcken in their game against Vittsjö GIK. This goal illustrates how Blackstenius can be instrumental in set pieces. The quality here lies in the way she gets away from her marker and gets that few centimeters she needs to attack the ball and head the ball in goal. The detail in the movement is what makes her better than other strikers in the Damallsvenskan.v

LOÏS OPENDA – DATA SCOUTING

Posted on 12/23/2021 by admin

In this scouting piece, I’m going to look at Vitesse’ Loïs Openda. I wanted to have a look at a striker who isn’t at the traditional top-3, but is performing very well. In this piece I’m purely focusing on match data and event data, to make a more data scouting report without the video. I will also relate this to his peers

The data
The data used in this analysis comes from Wyscout. In the dataset for the striker, I’ve selected each player who primarily plays on the striker position. Obviously, there are other players who have played in this position, but I’ve only selected the players that have played as a striker as a dominant position in the current season. This leaves me with 79 players who qualify in the Eredivisie 2021/2022.

Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me, it’s important that they played at least 600 minutes in this season. After looking at that I’m left with 42 players in my dataset and they will go through my analysis process. The data was retrieved on 23rd December 2021.

I will look at the following categories and metrics to assess their abilities through data:

Shots
Dribbling
Assists
Goals

Shots

In the scatterplot above you can see the number of shots per 90 of a certain player and the expected goals per 90 of that particular player in question. The reason we look at this is how many shots a player has in a game and how high the probability is of scoring an actual goal.

In the shot volume, we can see that Openda does quite well with 2,48 shots per 90 with an expected goal of 0,46 per game. Those two metrics are both above average as you can see. In the image below you can see Openda’s shot map of the 2021/2022 season with Vitesse so far.

Red = Goals, Grey = Grey

In the image above you can all shots, Openda had in the season so far. In those games, he has scored 10 times, twice from the penalty spot. He had 48 shots and a xG generated of 7,79 from those shots. With 10 goals scored, he’s overperforming with a number of +2,21 – a pretty good result. As you can see 9 goals came from within the penalty area, with only one coming outside of it. The sides are pretty evenly divided when looking at the goals, but in terms of shots, we can say two interesting things: he does shoot from distance more on the right side, but shoots from closer range on the left side.

Dribbling

Dribbling often is linked to wide midfielders of wingers, but it can be a valuable aspect of a striker’s game as well. The ability to control the ball, progress on the pitch, and deal positively with a 1v1 situation with an opponent defender, is not to be underestimated. Especially when you are not playing a typical central forward role, but playing with two strikers.

In the dribbles, we can see that Openda does quite average with 4,15 dribbles per 90 and a success rate of 55,7%. This does actually make him above average, but only just In the image below you can see Openda’s Ball Touch map of the 2021/2022 season with Vitesse so far.

In the image above you see the ball touches map of Openda in the opposition’s half. This is no dribble map, but it does illustrate where Openda gets the ball or touches the ball. In doing so we can see how much he’s closer to the midfield, how much he drops and plays deep – and how much he deviates from the natural striker position into the flanks. What we can conclude is that Openda does occupy the flanks a lot.

Passing

Expected metrics seem simple but can become incredibly complicated when combining things. In the scatterplot above I’ve taken a look at the probability of the pass becoming an assist per 90 minutes and looking at the actual assists of a player per 90 minutes.

In the assists, we can see that Openda does below average with 0,07 xA per 90 and actual assists of 0,06 xA%. As you can see he is performing below average and doesn’t really impress in the data. In the image below you can see Openda’s final third passing map of the 2021/2022 season with Vitesse so far.

In the image above you see all final third passes from Openda in the Eredivisie 2021/2022 – now this doesn’t say a lot about the actual performance, but it does tell us something about the successful passing of Openda. The passes to the penalty area aren’t that successful as you can tell by the red passes, but on the flanks and backward passes are quite successful.

Final thoughts
Data analysis or scouting alone isn’t enough to fully assess the qualities of a player. It should always go hand-in-hand with video and/or real-life eye tests. But it does give us the tools to make shortlists and back up our findings with data. In this case, we can see that Openda does really well in the shooting metrics, but has been on average and below average in the dribbling and assists metrics. Depending on the profile you have for a striker, he could be included or left out. The most important thing to remember is that this never can be seen in isolation but always has to been in relation to something bigger.

DATA SCOUTING DAMALLSVENSKAN: FINDING THE BEST STRIKER

Posted on 12/18/2021 by admin

There has been a lot of controversy in women’s football in the last few days. What is the best league and which league is better than the other? Bit of non-discussion in my opinion, but the most important thing in it all is the accessibility and visibility of the league. I think that the Swedish Damallsvenskan is a league which relatively good and produces strong talents, but due to visibility isn’t really hyped. That’s why I’m writing about it today.

In this scouting piece I’m going to look for a striker who’s good in the box, has volume in shots per 90 and looks to match or overperform his expected goals ratio.

Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me, it’s important that they played at least 600 minutes in this season. After looking at that I’m left with 38 players in my dataset and they will go through my analysis process. The data was retrieved on 18th December 2021.

I will look at the following categories and metrics to assess their abilities through data:

Shots
Dribbling
Offensive duels
Assists
Goals

After going through the data analysis and visualisation, I will make a shortlist of players who I think are worth keeping your eye on.

Shots
Looking at shot quality can be measured in different things. In the scatterplots below I will look at the volume of the shots and the expected goals that are generated through the shots.

In the shot volume, we can see that Blackstenius 4,82 shots per 90), Gielnik (3,99 shots per 90), and M. Larsson (3,89 shots per 90) stand out in terms of the number of shots.

The best performers in terms of the percentage of shots going on target are Jakobsson with 61,54% shots on target, Rogic with 60% shots on target, and M. Larsson with 54,35% shots on target.

In the scatterplot above you can see the number of shots per 90 of a certain player and the expected goals per 90 of that particular player in question. The reason we look at this is how many shots a player has in a game and how high the probability is of scoring an actual goal.

In the shot volume, we can see that Blackstenius 4,82 shots per 90), Gielnik (3,99 shots per 90), and M. Larsson (3,89 shots per 90) stand out in terms of the number of shots.

Looking at the expected goals generated per game we see the following players coming on top: Blackstenius with 0,81 xG per 90, M. Larsson with 0,8 xG per 90, and Lundin with 0,52 xG per 90.

Dribbling

If we look at the number of dribbles per 90, the following players come out on top of their respect metric: Jónsdóttir with 8,78 dribbles per 90, Kafaji with 8,34 dribbles per 90, and Eiríksdóttir with 8,12 dribbles per 90.

When we look closer to the success rate of the dribbles, we can see that a different set of players scores high – but attempt fewer dribbles per 90: Zamora with 67,5% successful dribbles, Scarpa with 65,38% successful dribbles, and Wangerheim with 65,12% successful dribbles.

Offensive duels

The importance of offensive duels can be seen in two lights. The first one, is to measure the physicality of a strikers and the ability to win offensive duels to create something out of an attack. The second one, is to engage in the pressing style set out by a team. The ability to press a direct opponent and win the ball can also be found in this metric of offensive duels.

The most offensive duels conducted per 90 are by the following players: Da Silva with 19,52 offensive duels per 90, Mijatovic with 19 offensive duels per 90, and Eiríksdóttir with 18,77 offensive duels per 90.

If we look closer at the players that have the highest percentage of won offensive duels, the following players stand out: Hellstrom with 39,52% offensive duels won, Gielnik with 39,17% offensive duels won, and Mijatovic with 39,09% offensive duels won.

Assists

If we look at the expected assists per 90, we can see that three players stand out from the crowd with a significantly higher xA per 90 than the rest. Jónsdóttir has 0,26 expected assists per 90, Jalkerud has 0,25 expected assists per 90, and M. Larsson/Mijatovic has 0,24 expected assists per 90.

Looking more closely, we can see that the actual assists per 90 don’t correspond with the three players with the highest expected assists per 90. Bredgaard has 0,33 assists per 90, Kapocs has 0,30 assists per 90, and Jalkerud/Mijatovic has 0,29 assists per 90.

Goals

In the end the most important thing for a striker is his output: goals. I’m looking at the probability of scoring a goal with a certain short and looking at the actual goals scored by a particular player per 90 minutes.

When we look more closely to the actual goals scored per 90 we see that Blackstenius stands out with 0,80 goals per 90, followed by Kanu with 0,7 goals per 90, and M. Larsson with 0,59 goals per 90.

Short list

Four players have impressed me in terms of data and I have made percentile ranks data visualisations of them, before going further and analysing them through video.

After this phase of data scouting and analysing, we will move into video scouting and assess how well they do in certain game situations. This article was an example of how you use data to make a shortlist.

DATA SCOUTING DUTCH TWEEDE DIVISIE (3RD TIER): FINDING A STRIKER

Posted on 12/11/2021 by admin

Day 11 of Blogmas and this time I’m going to cover the Dutch 3rd tier. I was very excited that I could find data on this league on Wyscout, because it is an amateur competition within a closed system, but on that latter part, I will write a different article.

In this article, however, I will use data to scout the best strikers in the Tweede Divisie and make a shortlist of which players are worth following in the next months to come.

Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me, it’s important that they played at least 600 minutes in this season. After looking at that I’m left with 23 players in my dataset and they will go through my analysis process. The data was retrieved on 18th September 2021.

I will look at the following categories and metrics to assess their abilities through data:

Shots
Dribbling
Offensive duels
Assists
Goals

After going through the data analysis and visualisation, I will make a shortlist of players who I think are worth keeping your eye on.

Shots
Looking at shot quality can be measured in different things. In the scatterplots below I will look at the volume of the shots and the expected goals that are generated through the shots.

In the shot volume, we can see that Castien (4,69 shots per 90), Van der Moot (3,59 shots per 90), and Brandsma (3,33 shots per 90) stand out in terms of the number of shots.

The best performers in terms of the percentage of shots going on target are Sanchez with 80% shots on target, Bitter with 80% shots on target, and Brandsma with 60% shots on target.

In the shot volume, we can see that Castien (4,69 shots per 90), Van der Moot (3,59 shots per 90), and Brandsma (3,33 shots per 90) stand out in terms of the number of shots.

Looking at the expected goals generated per game we see the following players coming on top: Van der Linden with 0,77 xG per 90, El Azzouti with 0,64 xG per 90, and Blommestijn with 0,59 xG per 90.

Dribbling

If we look at the number of dribbles per 90, the following players come out on top of their respect metric: Hardijk with 10,18 dribbles per 90, Admiraal with 7,82 dribbles per 90, and Sterling with 7,36 dribbles per 90.

When we look closer to the success rate of the dribbles, we can see that a different set of players scores high – but attempt fewer dribbles per 90: Poepon with 58,52% successful dribbles, Zeldenrust with 57,58% successful dribbles, and Bitter with 56% successful dribbles.

Offensive duels

The most offensive duels conducted per 90 are by the following players: Sterling with 16,47 offensive duels per 90, Hardijk with 16,12 offensive duels per 90, and Castien with 15,26 offensive duels per 90.

If we look closer at the players that have the highest percentage of won offensive duels, the following players stand out: Blij with 45,61% offensive duels won, Langedijk with 45% offensive duels won, and Sterling with 43,48% offensive duels won.

Assists

If we look at the expected assists per 90, we can see that four players stand out from the crowd with a significantly higher xA per 90 than the rest. Vink has 0,39 expected assists per 90, Kaptein has 0,41 expected assists per 90, and Castien has 0,32 expected assists per 90.

Looking more closely, we can see that the actual assists per 90 don’t correspond with the three players with the highest expected assists per 90. Vink has 0,74 assists per 90, Doesborg has 0.39 assists per 90, and Wouter/Zeldenrust has 0,38 assists per 90.

Goals

When we look more closely to the actual goals scored per 90 we see that Van der Linden stands out with 0,99 goals per 90, followed by Blommestijn with 0,94 goals per 90, and El Azzouti with 0,78 goals per 90.

Short list

Four players have impressed me in terms of data and I have made percentile ranks data visualisations of them, before going further and analysing them through video.

BARCELONA B 2021/2022: CHANCE CREATION FROM ZONE 14

Posted on 12/07/2021 by admin

I never thought I would write about Barcelona to be honest. So many people before have written about this club, but I thought that writing about their ‘B’ team would be quite interesting as they aren’t operating in a top 5 league, and it’s always good to see whether talents do well in a league that is full of senior players.

I will look more closely to how Barcelona B creates chances from zone 14 and I’m doing that by looking at video fragments of those chances in the 2021/2022 season in the Segunda Division B in Spain.

Zone 14

What is zone 14 and why is it important to many analysts? Spielverlagerung does explain it rather nicely:

“On a pitch divided into a six-by-three grid with a central strip as wide as the six yard box, the Zone 14, also called The Hole, has been classified as the rectangle which helps teams score more goals. Zone 14 is the zone located in the middle of the pitch immediately outside the opposing penalty area. During the 1990s and early 2000s, statistical data showed that successful teams such as the World Cup winning team of France or 1999 Champions League winner Manchester United had a better performance in Zone 14, as it was the key area which produced vast majority of passing assist. Until today, some prefer the concept of using Zone 14 as a target area in terms of build-up play, mostly denying the use of cross passes. According to various studies, the most effective way to use Zone 14 is to play a pass into the penalty area. Plus, the phase of possession in Zone 14 should not take longer than eight seconds.”

I like to look at zone 14 when I analyse teams. Not so much because I value zone 14 a lot, but I find it interesting to see which teams use that zone a lot and try to create goalscoring opportunities from there.

Chance creation: shooting

In the image above you see the pitch divided into 14 zones, which has been generated from InStat. In the current season, Barcelona B has created 82 chances, all of them in the final third. AS you can see chances have been created on the flanks, a stagger 71 chances within the penalty area and 7 have been created in that zone 14, we spoke about above. 8,54% of the chances were created from zone 14 and that’s what we are analysing in the next segment.

In the 3 videos above you can see how Barcelona B does shoot from zone 14. They often come in the situations by pressing the defenders, making sure that timing and place of the pressing is accurate, and regainin possession of the ball. In doing so they have 2-3 players in and around zone 14, which makes it easier to shoot from these locations. As you can see in the 3 videos above, the Barcelona outfit is quite successful when doing so in zone 14.

Zone 14 chance creation: passing

In the image above you can see the passes to the penalty area by Barcelona B per zone – this is a 14 zone grid. We see that the most passes come from the flanks, with 129 passes coming from the left and 102 passes from the right. As I’ve stated, I’m only interested in the zone 14 passes. In total there are 364 passes into the penalty area with 30 coming from zone 14, which is a percentage of 8,24%. Which is almost the same as the percentage for shots from zone 14.

What Barcelona B does very well in passing to the penalty area from zone 14 are two things. The first thing is that they want to dominate control of the ball in zone 14. They keep it in possession and try to play short passes within that zone to maintain control of the ball. The second thing they do well is that they try to look for that through ball or key pass that sets the attacking players up for a 1v1 or a good angle to shoot from. This isn’t always successful, but the intention is there and that’s why zone 14 can be very helpful in creating goalscoring opportunities.

Final thoughts

The main reason for creating this rather short article is to look at how Barcelona B does in zone 14 with chance creation. This is a very descriptive and quite obvious article, but it can also help in getting links. How do you use event data in combination with videos to analyse certain patterns of play? How do you contextualise and visualise chance creation?

SIMON ADINGRA: DRIBBLE & SHOT ANALYSIS 2021/2022

Posted on 12/05/2021 by admin

Today is the time for me to delve into a player playing in Denmark. There is a variety of talent in Denmark and I hadn’t taken a good look on my website at this league or the talents in it. I’m having a looking at this article at Nordsjællands’s Simon Adringra (19 years), focusing on his dribbles and shots.

In this analysis, I will zoom in on his attacking decisive actions during the 2021/2022 Danish Superliga in Denmark with the focus on dribbles and shooting stats from Wyscout/InStat data and then concentrating on some video fragments from Wyscout as well. In my dataset, I’ve chosen for all players playing on the striker position and have played over 600 minutes in the Superliga season. This leaves me with 26 players in my dataset to further go into the data analysis. I’m aware of the fact that often drifts to the left, but I wanted to analyse him in comparison to other strikers as he has played there a lot too.

Dribbles

In the image above you can see two metrics combined in a scatterplot. We look at the dribbles per 90 and the successful dribbles in percentages to look at two things. How many dribbles per 90 have been conducted per 90, and how high is the percentage of success at a particular player.

When we look at Adingra we can conclude that he has 9,92 dribbles per 90, which is above the average among strikers of 4,06. When we look at the percentage of dribbles that are successful we see that Adingra has a success rate of 50,91% which is just above the average of 43,94%.

I want to know where his dribbles have occurred during the season. I’m not as interested in the carries and where he finished the dribbling, but from which positions he started the dribbles. In the image below I’ve looked at the starting position of all dribbles he has attempted during the season.

As described above, you can see all the starting locations of the 98 dribbles Adingra had in the season. Of those 78 dribbles, 50,91% were successful, that’s roughly 50 dribbles that are successful. He has the most dribbles on the left side, with a fair number of dribbles starting in the middle third, but most of them in the attacking third. Further, we can assess that a lot of his dribbles start on the left of which we will give two examples below.

In the two videos above in the game against Midtjylland and Silkeborg, you see Adingra making a dribble with the starting location on the left. He then proceeds to make a 1v1 action and invert in order to find a shooting opportunity for himself or to find teammates who are having a better chance of creating something or having a go on goal themselves.

Shooting

I’ve added the metrics above to the profile to assess Adingra, because he has been instrumental in being a threat in front of goal. That’s why I’m looking at his numbers in shots per 90 and how many threat does shot pose – what is the probability of a shot being converted into a goal. This can be measured with the expected goals per 90 metric.

Adingra does quite well in these metrics as you can see in his position in the scatterplot. He has 3,34 shots per 90 and 0,29 expected goals per 90.

In the beeswarmplot above, you can see 6 metrics to assess a striker. It tells us how good Adingra is compared to his peers in each of these metrics. He performs quite well overall, but in the Non-penalty goals per 90, goal conversion and xG per 90 – he does very well.

The shootings stats in themselves show us the number of shots or type of shots or anything data related to the shots. Adingra does very well in those terms, but in the next part of the analysis, we want to look at where the shots actually came from and what that does tell about the position Adingra attempts to score a goal. Does he generate his xG from a few big chances? Or does he accumulate his xG by shooting a lot of low probable chances?

In the image below, we can see all of Adingra’s shots taken in the Superliga 2020/2021 season. There are 37 shots of which 5 have gone in goal which is a conversation rate of 13,51%. The image shows us the shot locations of the last 37 shots during the season and I will attempt to analyse which are most frequent.

Simon Adingra has scored 5 goals in the Superliga 2021-2022 season so far and had 37 shots in total. That is a goal conversion rate of 13,51%. From those 37 shots, 48,6% went on target. In the visual above you can see the shot locations of every shot attempted in the current season. In red, you see the goals and in grey the shots.

What we can conclude from this visual is that all of the goals are scored within the penalty area on the right side. We do see that he often attempts from the left side but isnt successful from that flank.

In the videos below I will have a look at the five goals scored by Adingra, showing how he preys on mistakes made by the opposition and will punish them.

In the video above you see how Nordsjælland has a counter attack but only Adingra is up top. His pace and the space to chase the last defender, gives him an advantage and he wins the ball. After he has done that he sets himself up nicely and shoots the ball calmly past the goalkeeper.

In the video above we see Nordsjælland in a smiliar situation from the first video, as we see them starting a counter attack. This time the ball isn’t directly played to Adingra, but he makes a third man run, which proves worthy in the end. He gets the ball in the central zones and has time to finish in the penalty area. He scored at the near post.

In this game from Nordsjælland we see that the opposition doesn’t deal with a high ball from Nordsjælland. Miscommunication between the central defenders and the goalkeeper, means that Adingra can profit from the error and he does this successfuly, scoring another goal after an error.

A very similar situation to the previous goal. He manages to stay close to the central defender and scan the space between the two central defenders. In doing so he manages to get to the ball quickly when the error comes and ultimately has a good finish which beats the goalkeeper: goal.

In the video above we Nordsjælland in possession of the ball when they begin their attack. The long ball from the keeper is recovered by the opposition but they are not aware of how high Nordsjælland’s attackers are. Again Adingra, makes the most of the error and has an opportunity to score – and does this brilliantly.

Final thoughts

Nordsjælland always has very interesting prospects and the talent is undeniable. In the case of Adingra I wanted to see how this attacker managed to use the space with dribbling and how his end product is. I think there is a huge talent to seen in this footballer, but he needs to work on efficiency of his actions. He often gets caught in wanting too much with his dribbles or his end product lacks the comfort of scoring goals. Yes he does score goals after errors, but he finds himself in situations where he might score more. Even though he is outperforming his xG of 3,27 and 5 goals – but this can be even better for the young attacker.

DATA SCOUTING POLISH EKSTRAKLASA 2021/2022: FINDING A CENTRAL DEFENDER

Posted on 12/03/2021 by admin

In the last data scouting piece I spoke about the fact that I wanted to look further than the usual countries in Europe and scouted the Finnish Veikkausliiga. Although I still stand by those words and wanted to broad my view, I came to realise that I’ve not really looked into certain countries in Europe that are worth looking into. My eye will focus more closely to the leagues in eastern Europe, this time I’m focusing on the Polish Ekstraklasa

Polish football does have enormous talents and players who develop into world class players, but how is football in the domestic league? In this article I will look more closely to the central defenders in that league.

In this scouting piece I’m going to look for a central defender with an accent for ball progressing capabilities. There are different types of central defenders, but I’m looking for a profile that fits a central defender who can carry the ball and thinks progressively.

The data
The data used in this analysis comes from Wyscout. In the dataset for the central defenders, I’ve selected each player who primarily plays on the central defender position. Obviously, there are other players who have played in this position, but I’ve only selected the players that have played as a central defender as a dominant position in the current season. This leaves me with 91 players who qualify in the Ekstraklasa 2020-2021.

Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me it’s important that they played at least 800 minutes in this season. After looking at that I’m left with 54 players in my dataset and they will go through my analysis process. The data was retrieved on 3rd December 2021.

I will look at the following categories and metrics to assess their abilities through data:

Defensive abilities:
Ball-carrying abilities
Passing abilities

Defensive abilities

The importance of defensive duels is evident. It’s to measure the physicality of a central defender and the ability to win defensive duels to assess how well a player defends in defensive situations.

The most defensive duels conducted per 90 are by the following players: Szczesńiak with 9,78 defensive duels per 90, Krivotsyuk with 8,90 defensive duels per 90, and Diogo Verdasca with 7,88 defensive duels per 90.

If we look closer at the players that have the highest percentage of won defensive duels, the following players stand out: Milic with 83,67% defensive duels won, Satka with 77,05% defensive duels won, and Cichocki with 76,47% defensive duels won.

The importance of aerial duels is to assess two things. Firstly, to look how many times a certain player conducts in an aerial duel during 90 minutes of football. And secondly, to assess how many of those aerial duels are won per 90. The aerial capability can be a contributing factor in the defensive strength of a central defender.

The most aerial duels conducted per 90 are by the following players: Golla with 6,91 aerial duels per 90, Petrasek with 6,88 aerial duels per 90, and Wieteska with 6,59 aerial duels per 90.

If we look closer at the players that have the highest percentage of won aerial duels, the following players stand out: Israel Puerto with 75% aerial duels won, Augustyn with 73,91% aerial duels won, and Petrasek with 73,85% aerial duels won.

In the scatterplot above we can see the metrics shots blocked per 90 and the interceptions per 90. These metrics help us assess the defending quality of a central defender, because it shows a form of an intelligence of a player. You have to recognise the movements of the opposition to adequately make a defensive actions, and therefore these metrics are useful.

The most shots blocked per 90 are by the following players: Raphael with 1,38 shots blocked per 90, Nalepa with 1,02 shots blocked per 90, and Maloca with 1,01 shots blocked per 90.

If we look closer at the players that have the most Interceptions per 90, the following players stand out: Tekijaski with 7,56 interceptions per 90, Nalepa with 7,27 interceptions per 90, and Ivanov with 6,91 interceptions per 90.

Ball-carrying abilities

Ball-carrying is a valuable thing for a player to have. The ability to literally carry the ball from the defensive third to the middle or attacking third is not to be underestimated, and this is no different for central defenders that I’m scouting. I’m well aware that this is not something every central defender can do, but I’m looking for a progressing central defender in possession. In what manner do they conduct themselves in progressing the ball? This can be translated via data with the metrics dribbles per 90 and progressive runs per 90.

If we look at the dribbles per 90 metrics, we can see that three players really stand out from the crowd here. Grzybek has 3,55 dribbles per 90, Tudor has 2,52 dribbles per 90 and Stiglec has 1,67 dribbles per 90.

When we look at the progressive runs per 90, we see slightly different players. The top players in this metric are: Gryszkiewicz has 2,04 progressive runs per 90, Wieteska has 1,91 progressive runs per 90, and Grzybek has 1,78 progressive runs per 90.

Passing ability

Passing abilities. I could focus on the percentage of successful passes, but that doesn’t say a lot in itself. I want to see how well they progress the ball as well as without the ball. I’ve looked to the progression with the ball on their feet, but I also want to see how well the progression in passing is. That’s why I chose to look at progressive passes per 90 and passes to the final third.

Looking at the progressive passes we see a few players stand out: Flis with 12,18 progressive passes per 90, Zech with 11,14 progressive passes per 90, and Israel Puerto with 10,85 progressive passes per 90.

If we look closer to the passes to the final third, we see some of the same names featured at the top. Flis has 9,6 passes to final third per 90, Sadlok has 9,41 passes to final third per 90, and Salamon has 7,90 passes to final third per 90.

DATA SCOUTING FINNISH VEIKKAUSLIIGA: FINDING A DEFENSIVE MIDFIELDER

Posted on 10/16/2021 by admin

I think that many scouting pieces or analysis pieces love to look at Scandinavia, but that Iceland and Finland are hugely underrepresented in those pieces. In this piece I will look at the Finnish Veikkaussliiga and concentrate on finding a defensive midfielder.

In this scouting piece I’m going to look for a defensive midfielder with an accent for defensive capabilities. There are different types of defensive midfielders, but I’m looking for a profile that fits a defensive midfielder who can carry the ball and thinks progressively.

The data
The data used in this analysis comes from Wyscout. In the dataset for the defensive midfielders, I’ve selected each player who primarily plays on the defensive midfield position. Obviously, there are other players who have played in this position, but I’ve only selected the players that have played as a defensive midfielder as a dominant position in the current season. This leaves me with 27 players who qualify in the Veikkausliiga Lig 2021.

Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me, it’s important that they played at least 900 minutes in this season. After looking at that I’m left with 21 players in my dataset and they will go through my analysis process. The data was retrieved on 16th October 2021.

I will look at the following categories and metrics to assess their abilities through data:

Defensive abilities:
Ball-carrying abilities
Passing abilities

After going through the data analysis and visualisation, I will make a shortlist of players who I think are worth keeping your eye on.

Defensive abilities

The importance of defensive duels is evident. It’s to measure the physicality of defensive midfielders and the ability to win defensive duels to assess how well a player defends in defensive situations. T

The most defensive duels conducted per 90 are by the following players: Purme with 10,04 defensive duels per 90, Malolo with 10,25 defensive duels per 90, and Arifi with 10,72 defensive duels per 90.

If we look closer at the players that have the highest percentage of won defensive duels, the following players stand out: Alejandro Sanz with 67,30% defensive duels won, Popovitch with 70,50% defensive duels won, and Adjei-Boateng with 70,94% defensive duels won.

The importance of aerial duels is to assess two things. Firstly, to look at how many times a certain player conducts in an aerial duel during 90 minutes of football. And secondly, to assess how many of those aerial duels are won per 90. The aerial capability can be a contributing factor in the defensive strength of a defensive midfielder.

The most aerial duels conducted per 90 are by the following players: Asier with 2,28 aerial duels per 90, Nurmela with 3,51 aerial duels per 90, and Bushue with 3,75 aerial duels per 90.

If we look closer at the players that have the highest percentage of won aerial duels, the following players stand out: Bushue with 64,58% aerial duels won, Annan with 72,73% aerial duels won, and Laaksonen with 76,47% aerial duels won.

Ball-carrying abilities

Ball-carrying is a valuable thing for a midfielder to have. The ability to literally carry the ball from the defensive third to the middle or attacking third is not to be underestimated, and this is not different for defensive midfielders that I’m scouting. In what manner do they conduct themselves in progressing the ball? This can translated via data with the metrics dribbles per 90 and progressive runs per 90.

If we look at the dribbles per 90 metric, we can see that three players really stand out from the crowd here. Laaksonen has 2,68 dribbles per 90, Purme has 3,18 dribbles per 90 and Ramandingaye has 2,42 dribbles per 90. They attempt to dribble a lot more than the average player does, which is near 1,66 dribbles per 90.

When we look at the progressive runs per 90, we see a similar kind of top-3. The top players in this metric are the same as above, but in a slightly different order. Popovitch has 1,25 progressive runs per 90, Ramandingaye has 1,32 progressive runs per 90 and Purme has 1,49 progressive runs per 90.

Passing ability

Looking at the progressive passes we see three players stand out: Adjei-Boateng with 8,89 progressive passes per 90, Nurmela with 9,15 progressive passes per 90, and Lingman with 9,38 progressive passes per 90.

If we look closer to the passes to the final third, we see some of the same names featured at the top. Arifi has 8,82 passes to final third per 90, Adjei-Boateng has 10,34 passes to final third per 90, and Lingman has 10,59 passes to final third per 90.

Short list

This data can change within a few weeks, but looking at the data at hand and the above visuals – I’ve made a shortlist of five players who are worth scouting a bit more in terms of video scouting:

Bismark Adjei-Boateng (27) – KuPS (now Cluj)
Tino Purme (23) – FC Haka
Anselmi Nurmela (24)- AC Oulu
Johannes Laaksonen (30) – FC KTP
Anton Popovitch (25) – KuPS

In my opinion these players would be up for further investigation and research in terms of videoscouting and profiling within the Finnish league.

Sources

Data: Wyscout
Visuals: Tableau Public

DATA SCOUTING NORWEGIAN ELITESERIEN 2021: FINDING A STRIKER

Posted on 09/19/2021 by admin

In the last data scouting piece I spoke about the fact that I wanted to look further than the usual countries in Europe and scouted the Austrian Bundesliga. Although I still stand by those words and wanted to broad my view, I came to realise that I’ve not really looked into certain countries in Europe that are worth looking into. My eye will focus more closely to the leagues in Portugal, Russia, Austria, Scandinavia and Turkey in the next weeks. Last time I spoke about Austria, today I will delve into the Norwegian Eliteserien.

In this scouting piece I’m going to look for a striker who’s good in the box, has volume in shots per 90 and looks to match or overachieve his expected goals ratio.

Because I’m looking at the current season, which is a full season, I want to make a selection for players that played a decent amount of games for me to assess them. For me, it’s important that they played at least 900 minutes in this season. After looking at that I’m left with 23 players in my dataset and they will go through my analysis process. The data was retrieved on 18th September 2021.

I will look at the following categories and metrics to assess their abilities through data:

Shots
Dribbling
Offensive duels
Assists
Goals

After going through the data analysis and visualisation, I will make a shortlist of players who I think are worth keeping your eye on.

Shots
Looking at shot quality can be measured in different things. In the scatterplots below I will look at the volume of the shots and the expected goals that are generated through the shots.

In the shot volume, we can see that Wadji (3,47 shots per 90), Friday (3,29 shots per 90), and Lauritsen (3,26 shots per 90) stand out in terms of the number of shots.

The best performers in terms of the percentage of shots going on target are Omijuanfo with 67,44% shots on target, Bakenga with 57,14% shots on target, and Tveter with 55,17% shots on target.

In the scatterplot above you can see the number of shots per 90 of a certain player and the expected goals per 90 of that particular player in question. The reason we look at this is how many shots a player has in a game and how high the probability is of scoring an actual goal.

In the shot volume, we can see that Wadji (3,47 shots per 90), Friday (3,29 shots per 90), and Lauritsen (3,26 shots per 90) stand out in terms of the number of shots.

Looking at the expected goals generated per game we see the following players coming on top: Wadji and Kone with 0,58 xG per 90, Bakenga with 0,7 xG per 90, and Omojiuanfo with 0,9 xG per 90.

Dribbling

If we look at the number of dribbles per 90, the following players come out on top of their respect metric: Taylor with 8,09 dribbles per 90, Friday with 5,59 dribbles per 90, and Mikkelsen with 5,33 dribbles per 90.

When we look closer to the success rate of the dribbles, we can see that a different set of players scores high – but attempt fewer dribbles per 90: Brustad with 81,82% successful dribbles, Bakenga with 75% successful dribbles, and Udahl with 71,43% successful dribbles.

Offensive duels

The most offensive duels conducted per 90 are by the following players: Friday with 18,09 offensive duels per 90, Liseth with 16,45 offensive duels per 90, and Taylor with 13,42 offensive duels per 90.

If we look closer at the players that have the highest percentage of won offensive duels, the following players stand out: Rasmussen with 59,21% offensive duels won, Mikkelsen with 47,51% offensive duels won, and Bakenga with 44,9% offensive duels won.

Assists

If we look at the expected assists per 90, we can see that four players stand out from the crowd with a significantly higher xA per 90 than the rest. Taylor has 0,27 expected assists per 90, Edvardsen has 0,14 expected assists per 90, and Brustad has 0,12 expected assists per 90.

Looking more closely, we can see that the actual assists per 90 don’t correspond with the three players with the highest expected assists per 90. Taylor has 0,31 assists per 90, Edvardsen has 0,25 assists per 90, and Berisha has 0,26 assists per 90.

Goals

In the end the most important thing for a striker is his output: goals. I’m looking at the probability of scoring a goal with a certain short and looking at the actual goals goals scored by a particular player per 90 minutes.

When we look more closely to the actual goals scored per 90 we see that Omojuanfo stands out with 1,33 goals per 90, followed by Bakenga with 1,06 goals per 90, and Lehne Olsen with 0,81 goals per 90.

Short list

Four players have impressed me in terms of data and I have made percentile ranks data visualisations of them, before going further and analysing them through video.